learning-to-summarize-with-human-feedback-8be1a186·1 events·first seen Aliases: Learning to Summarize with Human Feedback
OpenAI published research applying reinforcement learning from human feedback (RLHF) to train language models for improved summarization quality. The work demonstrated that models trained with human preference signals outperform those trained purely on supervised objectives for summarization tasks. This paper is an early foundational contribution to the RLHF methodology that later became central to aligning large language models.